Marko Kalinić

Computational classification models for predicting the interaction of drugs with P-glycoprotein and breast cancer resistance protein

P-glycoprotein (P-gp/ABCB1) and breast cancer resistance protein (BCRP/ABCG2) are two members of the adenosine triphosphate (ATP) binding cassette (ABC) family of transporters which function as membrane efflux transporters and display considerable substrate promiscuity. Both are known to significantly influence the absorption, distribution and elimination of drugs, mediate drug–drug interactions and contribute to multiple drug resistance (MDR) of cancer cells. Correspondingly, timely characterization of the interaction of novel leads and drug candidates with these two transporters is of great importance. In this study, several computational classification models for prediction of transport and inhibition of P-gp and BCRP, respectively, were developed based on newly compiled and critically evaluated experimental data. Artificial neural network (ANN) and support vector machine (SVM) ensemble based models were explored, as well as knowledge-based approaches to descriptor selection. The average overall classification accuracy of best performing models was 82% for P-gp transport, 88% for BCRP transport, 89% for P-gp inhibition and 87% for BCRP inhibition, determined across an array of different test sets. An analysis of substrate overlap between P-gp and BCRP was also performed. The accuracy, simplicity and interpretability of the proposed models suggest that they could be of significant utility in the drug discovery and development settings.

Structural insights into binding of small molecule inhibitors to Enhancer of Zeste Homolog 2

Enhancer of Zeste Homolog 2 (EZH2) is a SET domain protein lysine methyltransferase (PKMT) which has recently emerged as a chemically tractable and therapeutically promising epigenetic target, evidenced by the discovery and characterization of potent and highly selective EZH2 inhibitors. However, no experimental structures of the inhibitors co-crystallized to EZH2 have been resolved, and the structural basis for their activity and selectivity remains unknown. Considering the need to minimize cross-reactivity between prospective PKMT inhibitors, much can be learned from understanding the molecular basis for selective inhibition of EZH2. Thus, to elucidate the binding of small-molecule inhibitors to EZH2, we have developed a model of its fully-formed cofactor binding site and used it to carry out molecular dynamics simulations of protein–ligand complexes, followed by molecular mechanics/generalized born surface area calculations. The obtained results are in good agreement with biochemical inhibition data and reflect the structure–activity relationships of known ligands. Our findings suggest that the variable and flexible post-SET domain plays an important role in inhibitor binding, allowing possibly distinct binding modes of inhibitors with only small variations in their structure. Insights from this study present a good basis for design of novel and optimization of existing compounds targeting the cofactor binding site of EZH2.

Theoretical Models and QSRR in Retention Modeling of Eight Aminopyridines.

In this article, retention modeling of eight aminopyridines (synthesized and characterized at the Faculty of Pharmacy) in reversed-phase high performance liquid chromatography (RP-HPLC) was performed. No data related to their retention in the RP-HPLC system were found. Knowing that, it was recognized as very important to describe their retention behavior. The influences of pH of the mobile phase and the organic modifier content on the retention factors were investigated. Two theoretical models for the dependence of retention factor of organic modifier content were tested. Then, the most reliable and accurate prediction of log k was created, testing multiple linear regression model-quantitative structure-retention relationships (MLR-QSRR) and support vector regression machine-quantitative structure-retention relationships (SVM-QSRR). Initially, 400 descriptors were calculated, but four of them (POM, log D, M-SZX/RZX and m-RPCG) were included in the models. SVM-QSRR performed significantly better than the MLR model. Apart from aminopyridines, four structurally similar substances (indapamide, gliclazide, sulfamethoxazole and furosemide) were followed in the same chromatographic system. They were used as external validation set for the QSRR model (it performed well within its applicability domain, which was defined using a bounding box approach). After having described retention of eight aminopyridines with both theoretical and QSRR models, further investigations in this field can be conducted.

Influence of the mobile phase and molecular structure parameters on the retention behavior of protonated basic solutes in chaotropic chromatography

In this study, we present novel insights into the pH-dependent retention behavior of protonated basic solutes in chaotropic chromatography. To this end, two sets of experiments were performed to distinguish between mobile phase pH and ionic strength effects. In the first set, the ionic strength (I) was varied with the concentration of NaPF6 and additives that adjusted the mobile phase pH, while in the second set, I was kept constant by adding the appropriate amount of NaCl. In each set, the retention behavior of 13 analytes was qualitatively examined in 21 chromatographic systems, which were defined by the NaPF6 concentration in their aqueous phases (1-50mM) and the pH of their mobile phases (2, 3 or 4); the acetonitrile content was fixed at 40%. The addition of NaCl significantly reduced the differences among retention factors at studied pH values due to the effect of the Na+ ions on PF6-adsorption to the stationary phase and the magnitude of the consequential development of the surface potential. A quantitative description of the observed phenomenon was obtained by an extended thermodynamic approach. The contribution of ion-pair formation in the stationary phase to the retention of the solutes was confirmed across models at the studied pH values in the set with varying I. In the systems with a constant I, the shielding effect of the Na+ ions on the surface charge lowered the attractive surface potential and diminished the aforementioned interactions and hence the effect of the mobile phase pH on analyte retention. Eventually, we developed a readily interpretable empirical retention model that simultaneously takes into account analyte molecular structures and the most relevant chromatographic factors. Its coefficients have clear physical meaning, and owing to its good predictive capabilities, the model could be successfully used to clarify the contributions of analyte molecular structures and chromatographic factors to the specific processes underlying separation in chaotropic chromatography.

Synthesis, Cytotoxicity and Computational Study of Novel Protoberberine Derivatives

A novel and efficient synthetic route has been developed for the preparation of protoberberine derivatives. The methodology designed to control, primarily, substitution patterns on the terminal rings, was used to access a small array of these compounds. Initial biological profiling suggested anticancer potential of synthesised derivatives while structure-based target fishing has identified their potential targets and has established rational bases for further structural modifications. Although the activities need further improvement, our study demonstrated that the described approach may be useful in the discovery of the novel lead compounds.